Kalari, KR

Abstract Background: Tumorigenesis involves both genetic and epigenetic changes. Epigenetic alterations are reversible and are promising cancer therapeutic targets. Decitabine (5-aza-2'-deoxycytidine), a DNA methyltransferase inhibitor, is FDA approved for hematological malignancies. However, the effect of decitabine in breast cancer is not completely understood. Previous reports indicated that one decitabine mechanism involves regulation of protein levels for DNMT1, the major DNA methyltransferase that methylates hemimethylated CpG di-nucleotides in DNA. However, the E3 ligase involved in this process has not been identified. Whether decitabine also regulates DNMT3A and 3B in a similar fashion remains unclear. Therefore, our goals were to 1) understand mechanisms underlying decitabine action, 2) test the antitumor activity of decitabine in breast cancer models and 3) identify biomarkers associated with response to decitabine. Methods and Results: Western blots of breast cancer cell lines showed that DNMT1, DNMT3A, and DNMT3B protein levels decreased following decitabine treatment without a reduction in mRNA levels. Bioinformatic analysis of DNA methyltransferase sequences revealed a potential TRAF6 binding motif, and the interaction with TRAF6 (TNF receptor-associated factor 6) was confirmed by IP. TRAF6 functions as an E3 ligase. To determine whether TRAF6 might be the E3 ligase responsible for the degradation of DNMTs after decitabine treatment, we knocked down TRAF6 by RNA interference or knocked out the TRAF6 gene by CRISPR/Cas9. Down regulation of TRAF6 attenuated DNMT ubiquitination and increased DNMT protein levels, suggesting that TRAF6 might mediate proteasome-dependent degradation of all three DNMTs. This was further confirmed by reconstituting the knockout cells with WT and a TRAF6-C70A mutant, followed by assessing DNMT protein levels. Global DNA methylation was also increased after TRAF6 depletion and was confirmed in TRAF6 knock out cells in which DNMT levels were unaffected by decitabine. Cell cytotoxicity and colony forming assays showed that TRAF6 knockout cells were resistant to decitabine, suggesting that a major decitabine mechanism of action is through the regulation of TRAF6 which, in turn, degrades DNMTs, leading to decreased global methylation. Finally, decitabine significantly induced TRAF6 at both mRNA and protein levels, a process that might create positive feedback leading to increased degradation of DNMT proteins upon decitabine treatment. Based on these results, we further hypothesized that levels of the three DNMTs might influence decitabine response. Using 18 breast cancer patient derived xenograft (PDX) models, we found a wide range of DNMT protein levels regardless of ER/HER2 status. DNMT levels in the PDX models were directly associated with sensitivity to decitabine treatment, confirming our hypothesis. Conclusion: Our data showed that decitabine might be an effective agent for treating breast cancer and revealed a novel mechanism underlying decitabine treatment. Baseline DNMT protein levels may serve as a biomarker for predicting decitabine drug response. Citation Format: Yu J, Qin B, Boughey JC, Moyer AM, Visscher DW, Sinnwell JP, Yin P, Thompson KJ, Docter TJ, Kalari KR, Suman VJ, Wieben ED, Felten SJ, Conners AL, Jones KN, McLaughlin SA, Copland JA III, Moreno Aspitia A, Northfelt DW, Gray RJ, Ingle JN, Lou Z, Weinshilboum R, Goetz MP, Wang L. Regulation of DNA methyltransferases via TRAF6 determines breast cancer response to decitabine. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-51.

Abstract Background: Both HR deficiency and BRCA mutation status predict response to platinum-based therapy and BRCA mutation status predicts docetaxel resistance. However, the association of either biomarker with response to the individual elements of either AC or taxanes (T) is unknown since T is commonly given concomitantly with or after anthracyclines (A). We evaluated the association of HRD and BRCA mutation status with response to neoadjuvant weekly T followed by AC or (F)EC in high-risk breast cancer. Methods: We studied 140 high risk Stage I-III breast cancer patients (pts), enrolled in the breast cancer genome guided therapy study (BEAUTY), obtaining biopsies for DNA/RNA sequencing and MRI imaging to assess response to neoadjuvant weekly T (+trastuzumab+/-pertuzumab for HER2+ disease) followed by AC or (F)EC. Germline BRCA status and HR status of tumor samples (Myriad laboratories) were obtained. HR deficient tumor was defined as HRD score ≥42 or BRCA mutation. MRI response by changes in tumor size after 12 weeks of T was classified by WHO criteria. pCR was defined as ypT0/Tis ypN0. Both MRI response after T and pCR (after T and AC) were examined in terms of germline BRCA mutation (gBRCAmut vs. gBRCAwt) and tumor HR deficiency. Results: Of 140 pts enrolled, 8 withdrew consent and 2 carboplatin treated pts were excluded. Germline data were available for 124/130 pts. 12 patients had BRCA deleterious germline mutations (4 BRCA1, 8 BRCA2). MRI partial (PR)/complete response (CR) rate to T was 47.3% (95% CI: 37.8-57.0%) in the BRCAwt group and 66.7% (95% CI: 34.9-90.1%) in the BRCAmut group. No MRI CR's were observed in BRCA1 mut pts. In contrast, pCR rate was 50% in the 12 gBRCAmut pts (95% CI: 21.1-78.9%) and 31.3% in the 112 gBRCAwt pts (95% CI: 22.8-40.7%). HR deficiency status has thus far been determined for 74 pts: 26 pts have HD deficient tumors: 18 TNBC, 5 Luminal B, 2 ER-/HER2+; and 1 ER+/HER2+. Determination of HR deficiency is ongoing and will be reported for the full cohort in terms of 12 week MRI response to T and pCR to T+AC. HR deficientMolecular Subtypeyes (%)no (%)TBD (%)Luminal A0/112/11 (18.2)9/11 (81.8)Luminal B5/37 (13.5)13/37 (35.1)19/37 (51.3)Luminal NOS0/21/2 (50)1/2 (50)ER+/Her2+1/17 (5.8)14/17 (82.4)2/17 (11.8)ER-/Her2+2/20 (10)11/20 (55)7/20 (35)Triple Negative18/43 (41.9)6/43 (18.6)17/43 (39.5)germline BRCA statusMRI partial response after T (%)MRI complete response after T (%)pCR after T&AC (%)BRCA11/4 (25)0/42/4 (50)BRCA25/8 (62.5)2/8 (25)4/8 (50)BRCAwt35/112 (31.3)18/112 (16.1)35/112 (31.3) Conclusion: In the setting of neoadjuvant weekly T followed by AC, pCR rates were non-significantly higher in pts with BRCA1 mutations. While we observed no overall association between BRCA mutation status and response rates to taxanes; nearly all MRI responses to taxanes (partial and complete) were observed in the BRCA2 group. Prospective studies are needed to validate these findings and to determine whether BRCA status can be used to select therapy. HR deficiency is uncommon in luminal A and HER2+, frequent in TNBC, and the association of HRD with both MRI response to taxanes and pCR will be reported at the meeting. Citation Format: Boughey JC, Kalari KR, Suman VJ, McLaughlin SA, Moreno Aspitia A, Moyer AM, Northfelt DW, Gray RJ, Vedell PT, Tang X, Dockter TJ, Jones KN, Felten SJ, Conners AL, Hart SN, Visscher DW, Wieben ED, Ingle JN, Hartman A-R, Timms K, Elkin E, Jones J, Wang L, Weinshilboum RW, Goetz MP. Role of germline BRCA status and tumor homologous recombination (HR) deficiency in response to neoadjuvant weekly paclitaxel followed by anthracycline-based chemotherapy. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-29.

Abstract Background: Based upon the association between pathologic response and disease free survival, the neoadjuvant setting is increasingly being used for drug development. NGS has identified unique and recurrent genetic alterations in breast cancer (BC) that are potentially targetable; however, the clinical implications are mostly unknown. We developed a prospective neoadjuvant study (BEAUTY) in high risk BC patients (pts) using weekly T followed by anthracycline-based chemo wherein percutaneous tumor biopsies (PTB) are obtained before/during/after chemo for NGS and PDX. Our goal is to identify novel biomarkers/pathways and develop PDX to test new therapeutic approaches. Methods: Pts underwent PTB at baseline and after 12 wks of T. Response to T was defined based upon 12 week Ki-67: responder (<15%) vs non-responder (≥15%). Pts with histologic response and absence of invasive BC at 12 wks were classified as responders. NGS was performed using PTB/blood DNA (exome) and PTB (RNA seq). MRI response was classified using RECIST criteria. NGS data were used to identify somatic copy number variants (cnvs) and expressed single nucleotide variants (eSNVs). Non-SCID mice (estrogen supplemented) were implanted ≤ 30 minutes with PTB samples. Results: Of the first 78 pts, 44 have completed T. Here we focus on 18 pts with either triple negative or luminal B BC. Clinical characteristics according to Ki-67 response are shown in Table 1. Comparison of genomic alterations in BEAUTY pts with TCGA identified a greater overlap with copy number gains (73%) compared to deletions (40%), along with similar observations of mutations in TP53, PTEN, RYR2, and AKT1 genes. Association analysis of CNVs and eSNVs between responders/non-responders identified 33 genes (predominantly located in chromosomes 1, 8, 13) and 580 eSNVs (corresponding to 497 genes) with a p < 0.05. Differential gene expression (DGE) analysis of responders/non-responders identified 198 genes with a p-value < 0.05. Integrated analysis of 539 genes (CNVs, eSNVs and DGE) identified pathways such as TGF-beta, Jak-Stat, WNT and NOTCH signalling. PDX take rate was 44% [triple negative (6/10); Luminal B (2/8)]. PDX growth rate was significantly associated with clinical baseline Ki-67 (p = 0.00014). Conclusion: This is the first prospective study to demonstrate the feasibility of using PTB to obtain both NGS data and PDX in the neoadjuvant setting. PDX take rate is associated with BC subtype and baseline Ki-67. Studies are ongoing to 1) validate genes/pathways associated with treatment response in subsequent BEAUTY pts; 2) genomically characterize and assess PDX in vivo response to T and 3) Use NGS data to prioritize new drugs/drug combinations in PDX. Funded by Mayo Clinic Center for Individualized Medicine and MC Cancer Center. Clinical CharacteristicsOverallResponders: 12 week Ki-67 < 15% (n = 9)Non-Responders: 12 week Ki-67 ≥ 15% (n = 9)Median Age495345T stage T2/T314 (78%)7 (78%)7 (78%)Node Positive8 (44%)4 (44%)4 (44%)Triple negative10 (56%)6 (67%)4 (44%)Luminal B8 (44%)3 (33%)5 (56%)Ki-67 after 12 Weeks of T Median 5% (0-11%)Median 35% (17-60%)Complete/Partial MRI Response after T 6 (67%)2 (22%) Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-08-10.